Introduction to deep learning : from logical calculus to artificial intelligence / Sandro Skansi [electronic resource]
Material type:![Computer file](/opac-tmpl/lib/famfamfam/CF.png)
- 9783319730042 (E-book)
- Q 325.5 S52I 2018
Contents:
From logic to cognitive science -- Mathematical and computational prerequisites -- Machine learning Basics -- Feed-forward neural networks -- Modifications and extensions to a feed-forward neural network -- Convolutional neural networks -- Recurrent neural networks -- Autoencoders -- Neural language models -- An overview of different neural network architectures -- Conclusion
Item type | Current library | Collection | Shelving location | Call number | Status | Date due | Barcode | Item holds | Course reserves | |
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SPU Library, Bangkok (Main Campus) | Electronic Resources | On Display | Q 325.5 S52I 2018 (Browse shelf(Opens below)) | Available | 9783319730042 |
เทคโนโลยีปัญญาประดิษฐ์ (ARTIFICIAL INTELLIGENCE TECHNOLOGY) ภาคการศึกษาที่ 2 |
Total holds: 0
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Q 325.5 ภ414ว 2565 วิทยาการข้อมูลและการเรียนรู้เชิงลึก = Data science and deep learning / | Q 325.5 ภ414ว 2565 วิทยาการข้อมูลและการเรียนรู้เชิงลึก = Data science and deep learning / | Q 325.5 H37E 2009 The elements of statistical learning : data mining, inference, and prediction / | Q 325.5 S52I 2018 Introduction to deep learning : from logical calculus to artificial intelligence / | Q 325.5 T46T 1992 Techniques in computational learning : an introduction / | Q 325.5 W37M 2016 Machine learning refined foundations, algorithms, and applications / | Q 327 D82P 2001 Pattern classification / |
Includes bibliographical references and index
From logic to cognitive science -- Mathematical and computational prerequisites -- Machine learning Basics -- Feed-forward neural networks -- Modifications and extensions to a feed-forward neural network -- Convolutional neural networks -- Recurrent neural networks -- Autoencoders -- Neural language models -- An overview of different neural network architectures -- Conclusion
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